Lotus Metasurface for Wide-Angle Intermediate-Frequency Water–Air Acoustic Transmission
Bibliographic record
Abstract
Only 0.1% of the acoustic energy can transmit across the water-air interface because of the huge acoustic impedance mismatch. Enhancing acoustic transmission across the water-air interface is of great significance for sonar communications and sensing. However, due to the interface instability and subwavelength characteristics of acoustic metamaterials, wide-angle intermediate-frequency (10 kHz-100 kHz) water-air acoustic transmission remains a great challenge. Here, we demonstrate that the lotus leaf is a natural low-cost acoustic transmission metasurface, namely, the lotus acoustic metasurface (LAM). Experiments demonstrate the LAM can enhance the acoustic transmission across the water-air interface, with an energy transmission coefficient of about 40% at 28 kHz. Furthermore, by fabricating artificial LAMs, the operating frequencies can be flexibly adjusted. Also, the LAM allows a wide-angle water-to-air acoustic transmission. It will enable various promising applications, such as detecting and imaging underwater objects from the air, communicating between ocean and atmosphere, reducing ocean noises, etc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".